Evaluating the quality of research activities: Investigating into the uniqueness
https://doi.org/10.33186/1027-3689-2018-10-5-21
Abstract
Today, the research activities of scientists and research organizations is estimated through the informetrical methods (bibliometrics) with absolute and relative indicators based on the number of publications and their citations in scientometric databases. The leading authors
and research organizations are given grants and awards, become international laureates, get financial support or other dividends. The authors argue that the method of research activities evaluation influences the authors’ behavior and increases plagiarism, rigged citation and academic dishonesty.
The fraud practices misrepresent the estimations of research activities quality and the current status of a discipline and publication activities. The problem is analyzed; simultaneous use of bibliometric methods and most advanced scientific methods of modern methods of defining writing styles is suggested as a solution. The authors emphasize that traditionally libraries are meant to educate, to popularize knowledge and to inform. Today, they have to go into non-traditional functions, i.e. to support linguistic research and to build linguistic corpora. This would prevent manipulations when estimating publication activities with bibliometric methods and would promote academic honesty in academic practices.
About the Authors
Yu. N. GlavchevaUkraine
Yulia Glavcheva, Deputy Director, Sci-tech Library
2, Kirpicheva st., 61144 Kharkov
O. V. Kanishcheva
Ukraine
Olga Kanishcheva, Cand. Sc. (Engineering), Dean
2, Kirpicheva st., 61144 Kharkov
M. I. Glavchev
Ukraine
Maxim Glavchev, Cand. Sc. (Economics), Professor, Dean, Sci-tech Library
2, Kirpicheva st., 61144 Kharkov
References
1. Mohnacheva Yu. V. O publikatsionnyh potokah mediko-biologicheskogo profilya na primere NII Federalnogo agentstva nauchnyh organizatsiy Rossii / Yu. V. Mohnacheva, V. A. Tsvetkova // Inform. i innovatsii. – 2017. – № 1–2. – S. 61–69.
2. Arutyunov V. V. O nekotoryh itogah otsenki rezultativnosti nauchnoy deyatelnosti natsionalnyh issledovatelskih universitetov Rossii / V. V. Arutyunov // Tam zhe. – 2017. – Spets. vyp. – S. 22–25.
3. International Mathematical Union (IMU) [Elektronnyy resurs]. – https://www.mathunion.org/
4. Research Excellence Framework. [Elektronnyy resurs]. – https://www.ref.ac.uk
5. Snowball Metrics – Standardized research metrics – by the sector for the sector Snowball Metrics [Elektronnyy resurs]. – https://www.snowballmetrics.com/
6. Zemskov A. I. Osnovnye zadachi bibliotek v oblasti bibliometrii / A. I. Zemskov // Inform. i innovatsii. – 2017. – Spets. vyp. – S. 79–83.
7. International Center for Academic Integrity [Elektronnyy resurs]. – http://www.academicintegrity.org/icai/integrity-3.php
8. Епідемія академічного плагіату в цифрах [Elektronnyy resurs]. – http://studway.com.ua/plagiat-2/
9. Guskov A. E. Rossiyskaya naukometriya: obzor issledovaniy / A. E. Guskov // Bibliosfera. – 2015. – № 3. – S. 75–86.
10. Lutsenko E. V. Kolichestvennaya otsenka stepeni manipulirovaniya indeksom Hirsha i ego modifikatsiya, ustoychivaya k manipulirovaniyu / E. V. Lutsenko, A. I. Orlov // Politemat. setevoy elektron. nauch. zhurn. Kuban. gos. agrar. un-ta. – 2016. – № 121. – S. 202–234.
11. Loyko V. I. Sovremennye podhody v naukometrii : monogr. / V. I. Loyko, E. V. Lutsenko, A. I. Orlov; pod nauch. red. prof. S. G. Falko. – Krasnodar : KubGAU, 2017. – 532 s.
12. Levin V. I. Novyy podhod k otsenke kachestva nauchnyh issledovaniy / V. I. Levin // Vysshee obrazovanie v Rossii. – 2017. – № 6. – S. 136–146.
13. Zemskov A. I. O nekotoryh bibliometricheskih indeksah / A. I. Zemskov // Nauch. i tehn. b-ki. – 2016. – № 8. – S. 18–28.
14. Beall's List of Predatory Journal sand Publishers [Elektronnyy resurs]. – https://beallslist.weebly.com/
15. Borgoyakova K. S. Bibliometriya i «ohota na hishchnikov» / K. S. Borgoyakova, A. I. Zemskov // Nauch. i tehn. b-ki. – 2018. – № 2. – S. 89–100.
16. Tsvetkova V. A. Bibliometricheskie pokazateli, publikatsionnaya aktivnost i publikatsii /V. A. Tsvetkova, Yu. V. Mohnacheva // Inform. i innovatsii. – 2017. – Spets. vyp. – S. 127–131.
17. Geoffrey Bill «Warning: essential information predatory journals» : [prezentatsiya uchastnika konferentsii «Informatsionnaya podderzhka nauki i obrazovaniya: naukometriya i bibliometriya»] / Bill Geoffrey // Tam zhe. – S. 137–147.
18. López-Cózar E. D. Manipulating Google Scholar citations and Google Scholar metrics: Simple, easy and tempting / E. D. López-Cózar, N. Robinson-Garcia, D.Torres-Salinas // arXiv preprint arXiv:1212.0638. – 2012.
19. Nalimov V. V. Naukometriya: izuchenie razvitiya nauki kak informatsionnogo protsessa /V. V. Nalimov, Z. M. Mulchenko. – Moskva : Nauka, 1969. – 192 s.
20. Gerasimov S. V. Instrumentalnye sredstva otsenki kachestva nauchno-tehnicheskih dokumentov /S. V. Gerasimov i dr. // Tr. In-ta sistem. programmirovaniya RAN. – 2013. – T. 24. – S. 359–380.
21. Ionenkov Yu. S. Otsenka kachestva nauchno-tehnicheskoy dokumentatsii / Yu. S. Ionenkov // ITNOU: inform. tehnologii v nauke, obrazovanii iupr. – 2017. – № 4 (4). – S. 14–18.
22. European Educational Research Quality Indicators. Project Final Report [Elektronnyy resurs]. – http://eerqi.eu/sites/default/files/Final_Report.pdf
23. Rollins Dzheyson E. «BigData for Innovation&Scientific Insight» : [prezentatsiya uchastnika konferentsii «Informatsionnaya podderzhka nauki i obrazovaniya: naukometriya i bibliometriya»] / Dzheyson E. Rollins // Inform. i innovatsii. – 2017. – Spets. vyp. – S. 153–160.
24. Derbenev N. V. Chto mozhno uluchshit v naukometricheskom analize – uchet nalichiya dublikatov i zaimstvovaniy v nauchnyh publikatsiyah / N. V. Derbenev, V. O. Tolcheev // Upr. bolshimi sistemami : sb. tr. – 2013. – № 44. – S. 366–380.
25. Mikolov T. Efficient Estimation of Word Representations in Vector Space / Mikolov T. et al. // arXiv preprint arXiv:1301.3781. – 2013.
26. Mikolov T. Linguistic regularities in continuous space word representations / T. Mikolov, W. Yih, G. Zweig // Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. – 2013. – С. 746–751.
27. AlSallal M. An integrated approach for intrinsic plagiarism detection / AlSallal M. et al. // Future Generation Computer Systems. – 2017. – https://doi.org/10.1016/j.future.2017.11.023.
28. Kanіshcheva O. V. Viznachennya stilyu avtora dlya viyavlennya plagіatu v akademіchnomu seredovishchі / O. V. Kanіshcheva, Yu. N. Glavcheva, V. A. Visotska // Sistemniy analіz ta іnformatsіynі tehnlogії : materіali 19-ї Mіzhnar. nauk.-tehnіchn. konf. SAIT 2017, 22–25 travnya 2017. – Kiїv : NNK «ІPSA» NTUU «KPІ» іm. Іgorya Sіkorskogo, 2017. – S. 78–79.
29. Kozlova N. V. Leengvisticheskie korpusa: opredelenie osnovnyh ponyatiy i tipologiya / N. V. Kozlova // Vestn. Novosib. gos. un-ta. Ser.: Leengvistika i mezhkultur. kommunikatsiya. – 2013. – T. 11. – № 1. – S. 79–88.
30. Tsvetkova V. A. Eshche nemnogo o Rossiyskom indekse nauchnogo tsitirovaniya (RINTS) / Tsvetkova V. A., Kalashnikova G. V. // Kultura: teoriya i praktika. – 2016. – № 5–6.
31. Bar-Ilan J. Informetrics at the beginning of the 21st century – A review / J. Bar-Ilan // Journal of Informetrics. – 2008. – № 2. – С. 1–52. – DOI:10.1016/j.joi.2007.11.001
32. Börner K. Visualizing knowledge domains / K. Börner, C. M. Chen, K. W. Boyack // Annual Review of Information Science and Technology. – 2003. – Випуск 37. – С. 179–255.
33. Garfield E. Historiographic mapping of knowledge domains literature / E. Garfield // Journal of Information Science. – 2004. – № 30 (2). – С. 119–145.
34. Kostoff R. Citation mining – Integrating text mining and bibliometrics for research user profiling / R. N. Kostoff, J. A. Rió, J. A. Humenik, E. O. García, A. M. Ramírez // Journal of the American Society for Information Science and Technology. – 2001. – № 52 (13). – С. 1148–1156.
35. Kostoff R. N. Fullerene data mining using bibliometrics and database tomography / R. N. Kostoff, T. Braun, A. Schubert, D. R. Toothman, J. A. Humenik // Journal of Chemical Information and Computer Sciences. – 2000. – № 40 (1). – С. 19–39.
36. Albert R. Statistical mechanics of complex networks / R. Albert, A. L. Barabási // Reviews of Modern Physics. – 2002. – № 74 (1). – С. 47–97.
37. Girvan M. Community structure in social and biological networks / M. Girvan, M. E. Newman // Proceedings of the National Academy of Sciences of the United States of America. – 2002. – № 99 (12). – С. 7821–7826.
38. Pudovkin A. I. Algorithmic procedure for finding semantically related journals / A. I. Pudovkin, E. Garfield // Journal of the American Society for Information Science and Technology. – 2002. – № 53 (13). – С. 1113–1119.
39. Glänzel W. A new classification scheme of science fields and subfields designed for scientometric evaluation purposes / W. Glänzel, A. Schubert // Scientometrics. – 2003. – № 56 (3). – С. 357–367.
40. Tsvetkova V. A. Sistemy tsitirovaniya: gde blago, gde zlo / V. A. Tsvetkova // Nauch. i tehn. b-ki. – 2015. – № 1. – S. 18–22.
Review
For citations:
Glavcheva Yu.N., Kanishcheva O.V., Glavchev M.I. Evaluating the quality of research activities: Investigating into the uniqueness. Scientific and Technical Libraries. 2018;(10):5-21. (In Russ.) https://doi.org/10.33186/1027-3689-2018-10-5-21